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Simultaneous Approximation of Multi-criteria Submodular Function Maximization
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作者 Dong-Lei Du Yu Li +1 位作者 Nai-Hua Xiu Da-Chuan Xu 《Journal of the Operations Research Society of China》 EI 2014年第3期271-290,共20页
Recently intensive interest has been raised on approximation of the NPhard submodular maximization problem due to their theoretical and practical significance.In this work,we extend this line of research by focusing o... Recently intensive interest has been raised on approximation of the NPhard submodular maximization problem due to their theoretical and practical significance.In this work,we extend this line of research by focusing on the simultaneous approximation of multiple submodular function maximization.We address the existence and nonexistence results for both deterministic and randomized approximation when the submodular functions are symmetric and asymmetric,respectively,along with algorithmic corollaries.We offer complete characterization of the symmetric case and partial results on the asymmetric case. 展开更多
关键词 MULTI-CRITERIA submodular function maximization Approximation algorithm EXISTENCE
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Optimizing top-k retrieval: submodularity analysis and search strategies 被引量:1
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作者 Chaofeng SHA Keqiang WANG +2 位作者 Dell ZHANG Xiaoling WANG Aoying ZHOU 《Frontiers of Computer Science》 SCIE EI CSCD 2016年第3期477-487,共11页
The key issue in top-k retrieval, finding a set of k documents (from a large document collection) that can best answer a user's query, is to strike the optimal balance between relevance and diversity. In this paper... The key issue in top-k retrieval, finding a set of k documents (from a large document collection) that can best answer a user's query, is to strike the optimal balance between relevance and diversity. In this paper, we study the top-k re- trieval problem in the framework of facility location analysis and prove he submodularity of that objective function which provides a theoretical approximation guarantee of factor 1 -1/ε for the (best-first) greedy search algorithm. Furthermore, we propose a two-stage hybrid search strategy which first ob- tains a high-quality initial set of top-k documents via greedy search, and then refines that result set iteratively via local search. Experiments on two large TREC benchmark datasets show that our two-stage hybrid search strategy approach can supersede the existing ones effectively and efficiently. 展开更多
关键词 top-k retrieval DIVERSIFICATION submodular function maximization
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